Collection · MT5

Kecoma Trading Collection

by kecoma1

This repository provides a collection of Expert Advisors for MetaTrader 5 and Python trading scripts developed for an educational YouTube series.

GitHub stars140
Forks94
Last update3 years ago23 Jul 2023
LicenceNone stated

Overview

Kecoma Trading Collection features various technical indicator-based strategies, including MACD, Relative Strength Index, Stochastic, and Bollinger Bands. The included MQL5 files implement multi-timeframe analysis, exponential moving average crossovers, and price action logic to identify market highs and lows. The code demonstrates how to handle indicator data, manage trades using the MQL5 trade class, and detect MACD divergence patterns. The repository is primarily designed as a learning resource rather than a single production-ready robot.

Details

Author

kecoma1 on GitHub

Type

Collection

Platform

MetaTrader 5 (MQL5)

Strategy

Indicator crossover, Mean reversion, Trend following, Multi-strategy

Markets

Crypto, Forex

Timeframes

Any timeframe

Risk profile

No grid, martingale or hedging logic was found in its code or README. That says nothing about how it performs: backtest it first.

Topics

trading-bottrading-algorithmsmetatrader5pythontradingbotmql5javacbinance-api

How to install it

  1. 1Download the sourceUse "Download source (.zip)" above, or clone kecoma1/Trading_BOT from GitHub, and unzip it.
  2. 2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
  3. 3Copy the filesCopy the .mq5 file into Experts.
  4. 4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
  5. 5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.

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